Blind and total identification of ARMA mode in higher ordercumulants domain

A novel recursive algorithm for identifying orders and parameters of ARMA models driven by a sequence of nonGaussian random signals is investigated. The input sequence is assumed to be unobservable and the conditions are based on properties of the model output cumulants of the third order. In every cycle of updating the model order, the proposed algorithm minimizes a quadratic cost function to determine the parameters. The novelty of the approach is that the model orders and parameters are all estimated without a priori knowledge; the system is blind. The identification process is said to be total because the model parameters together with the model order are estimated in the same process. Owing to its order-recursive nature, the proposed algorithm requires little computational complexity and exhibits fast convergence behavior. Simulation results verify that Gaussian noises present at the output do not have noticeable effects on the identifiability and the accuracy of estimation     

Activity Measures for Fast Relative Power Estimation in Numerical Transformation for Low Power DSP Synthesis

In this paper, we propose a method for power optimization of digital signal processing (DSP) systems through reduction of circuit switching activity estimated from high levels in the synthesis hierarchy, namely at numerical and algorithmic levels. The optimization involves application of a numerical transformation called number-splitting on the system characteristic coefficients. The transformation alters the system characteristic coefficients while preserving the input/output relations. For each set of candidate coefficients, the corresponding signal flow-graph is constructed for evaluation of power consumption. First, the switching activity at all computation nodes of the graph are estimated using our novel activity transformation models, which quickly estimate the activity at the output of the adders and multipliers based on the activity at the inputs. Next, the activity at the inputs of each computation node are used to compute the average power consumption by that node, using our heuristic power estimators.The optimization framework can be applied to hardware-dedicated bit-serial, nibble-serial, as well as programmable word-parallel architectures. We focus on hardware-dedicated bit-serial systems, and show that up to 35 percent savings in power is achievable.     

Performance Analysis of Adaptive Path Selective Decorrelating Detector with Channel Estimation Errors

The system complexity and noise enhancement due to the use of Multipath Decorrelating Detector (MDD) can be reduced by employing adaptive path selection technique. Adaptive Path Selective Decorrelating Detector (APSDD) requires knowledge of the channel coefficients for path selection. Generally, the channel coefficients are assumed to be known at the receiver. However, this is not realistic and the channel coefficients should be estimated. In this paper, we extend the Bit Error Rate (BER) analysis of the path selective receiver to include channel estimation errors.     

Design and multiplier-less implementation of a class of two-channel PR FIR filterbanks and wavelets with low system delay

A new method for designing two-channel PR FIR filterbanks with low system delay is proposed. It is based on the generalization of the structure previously proposed by Phoong et al. (1995) Such structurally PR filterbanks are parameterized by two functions (/spl beta/(z) and /spl alpha/(z)) that can be chosen as linear-phase FIR or allpass functions to construct FIR/IIR filterbanks with good frequency characteristics. The case of using identical /spl beta/(z) and /spl alpha/(z) was considered by Phoong et al. with the delay parameter M chosen as 2N-1. In this paper, the more general ease of using different nonlinear-phase FIR functions for /spl beta/(z) and /spl alpha/(z) is studied. As the linear-phase constraint is relaxed, the lengths of /spl beta/(z) and /spl alpha/(z) are no longer restricted by the delay parameters of the filterbanks. Hence, higher stopband attenuation can still be achieved at low system delay. The design of the proposed low-delay filterbanks is formulated as a complex polynomial approximation problem, which can be solved by the Remez exchange algorithm or analytic formula with very low complexity. In addition, the orders and delay parameters can be estimated from the given filter specifications using a simple empirical formula. Therefore, low-delay two-channel PR filterbanks with flexible stopband attenuation and cutoff frequencies can be designed using existing filter design algorithms. The generalization of the present approach to the design of a class of wavelet bases associated with these low-delay filterbanks and its multiplier-less implementation using the sum of powers-of-two coefficients are also studied.     

On the robustness of decision-feedback detection of DPSK and differential unitary space-time modulation in Rayleigh-fading channels

Decision-feedback differential detection (DFDD) of differential phase-shift keying (DPSK) and differential unitary space-time modulation (DUST) in Rayleigh-fading channels exhibits significant performance improvement over standard single-symbol maximum-likelihood detection. However, knowledge of channel fading correlation and signal-to-noise ratio (SNR) is required at the receiver to compute the feedback coefficients used in DFDD. In this letter, we investigate the robustness of the DFDD to imperfect knowledge of the feedback coefficients by modeling the mismatch between estimated feedback coefficients and ideal coefficients in terms of mismatch between the estimated values of fading correlation and SNR and the true values. Under the assumption of a block-fading channel when nondiagonal DUST constellations are used and a continuous fading channel otherwise, we derive exact and Chernoff bound expressions for pair-wise word-error probability and then use them to approximate the bit-error rate (BER), finding close agreement with simulation results. The relationships between BER performance and various system parameters, e.g., DFDD length and Doppler mismatch, are also explored. Furthermore, the existence of an error floor in the BER-vs-SNR curve is investigated for the infinite-length DFDD. For the special case of Jakes' fading model, it is shown that the error floor can be removed completely even when the Doppler spread is over-estimated.     

POWER-Area-Performance Characteristics of FPGA-based Sigma-Delta FIR Filters

While one-bit ΣΔ modulators are widely used in Analog to Digital conversion stages due to their inherent linearity and precision, it is less common for the entire digital processing path to operate in single bit mode at the oversampled rate of the conversion system. The conventional approach has been to decimate the signal bit stream after conversion and for the remaining processing to be performed in standard multi-bit binary at the Nyquist rate and with a resolution mandated by the dynamic range and noise. Using a Finite Impulse Response filter design as an example, we compare the area and performance of this conventional approach with the alternative single bit approach that operates directly on the ΣΔ data stream using ternary coefficients {?1, 0, +1} derived from the ΣΔ modulation of the target impulse response. Filters exhibiting approximately equivalent spectral performance in the two alternative approaches were developed using VHDL and simulated using some commercial FPGA types. In these experiments, the single-bit filters using ternary coefficients were found to dissipate less power compared to the conventional approach despite their need to operate at much higher clock rates. They also exhibit up to 40% higher performance and offer useful area savings at lower filter orders. At higher orders, the ΣΔ approach retains its power and performance advantages but exhibits slightly higher chip area. The simplicity and low power of the ΣΔ approach makes it applicable to mobile communication processing using low cost FPGA technology.     

Blind input, initial state, and system identification of SIMO Laguerre systems

Laguerre filters have infinite impulse responses (IIRs) but with finite tapped delay-line parameterizations. This paper investigates subspace-based blind identification of Laguerre filter tap coefficients, the internal filter state, and the input, given only noisy observations of the output. This paper deals only with single-input, multiple-output (SIMO) Laguerre models. A state space model for the SIMO Laguerre system is derived from which blind estimation algorithms are developed. As in the finite impulse response (FIR) case, the Laguerre filter taps coefficients can be estimated from the column space of a certain Hankel matrix constructed from noisy output observations, whereas the internal state and input can be estimated from the row space by exploiting state space structure. While not exactly uniquely identifiable, conditions are given for which the tap coefficients, the internal state, and the input can be determined to within a multiplicative scalar factor.     

Scattering from lossy dielectric objects buried beneath randomlyrough ground: validating the semi-analytic mode matching algorithm with2-D FDFD

A new semi-analytic mode matching (SAMM) algorithm is verified by two-dimensional (2-D) finite difference frequency domain (FDFD) simulations of scattering resulting from uniform plane waves incident on randomly rough dielectric half-spaces containing buried dielectric targets. The SAMM algorithm uses moderately low-order modal superpositions of cylindrical waves, each of which satisfies the 2-D-Helmholtz equation in its appropriate region (air, ground, or mine) and then matches all nonzero electric and magnetic field components at each interface by inverting a highly overconstrained dense linear matrix equation by singular value decomposition. That is, the set of cylindrical mode coefficients is found which best fits the boundary conditions in a least squares sense. For smooth ground, coordinate scattering centers (CSCs) are chosen at the mine center and at its image above the plane to model scattering. For randomly rough ground, additional CSCs are located within the rough boundary layer. Excellent agreement between 2-D-FDFD and the 2-D version of SAMM is observed, with 2-D-SAMM being at least an order of magnitude faster. 3-D-SAMM is estimated to be four orders of magnitude faster than 3-D-FDFD, with drastically reduced memory requirements     

Blind identification of bilinear systems

This paper is concerned with the blind identification of a class of bilinear systems excited by non-Gaussian higher order white noise. The matrix of coefficients of mixed input-output terms of the bilinear system model is assumed to be triangular in this work. Under the additional assumption that the system output is corrupted by Gaussian measurement noise, we derive an exact parameter estimation procedure based on the output cumulants of orders up to four. Results of the simulation experiments presented in the paper demonstrate the validity and usefulness of our approach.     

An algorithm for pole-zero system model order estimation

In system identification, estimates of the unknown system model orders are often required. An algorithm for estimating model orders is described that looks at input/output data covariance matrix eigenvectors. When model orders are overestimated, zeros appear in the noise subspace eigenvectors. The number of zeros present can be used to estimate model orders     

Identification of rod dynamics under influence of Active Magnetic Bearing

The purpose of this paper is to apply the wavelet transform algorithm to identify the magnetic damping and magnetic stiffness coefficients of the drive rod with which a set of 4-pole Active Magnetic Bearing (AMB) is equipped. By taking advantage of time–frequency analysis feature, the ridge curve of rod free response after wavelet transformation can be extracted to find the natural frequency of the rod/AMB system. In other words, due to the influence of magnetized field by the AMB, the stiffness of the rod dynamics is not linear any more and can be estimated from the curve of the amplitude versus frequency by wavelet transformation. On the other hand, the nonlinear damping coefficients can be estimated from the derivative of amplitude versus amplitude by wavelet transformation of rod free vibration. It is found that the nonlinear magnetic damping coefficients are up to 2nd-order in polynomial and the stiffness coefficient is mainly of 3rd-order respectively. In addition, the identified 2nd-order damping coefficient is negative and hence implies that under specific rod displacement and speed, the dynamic of the rod/AMB system in axial direction is unstable.     

A New Training Approach for Parametric Modeling of Microwave Passive Components Using Combined Neural Networks and Transfer Functions

This paper presents a novel technique to develop combined neural network and transfer function models for parametric modeling of passive components. In this technique, the neural network is trained to map geometrical variables onto coefficients of transfer functions. A major advance is achieved in resolving the discontinuity problem of numerical solutions of the coefficients with respect to the geometrical variables. Minimum orders of transfer functions for different regions of geometrical parameter space are identified. Our investigations show that varied orders used for different regions result in the discontinuity of coefficients. The gaps between orders are bridged by a new order-changing module, which guarantees the continuity of coefficients and simultaneously maintains the modeling accuracy through a neural network optimization process. This technique is also expanded to include bilinear transfer functions. Once trained, the model provides accurate and fast prediction of the electromagnetic behavior of passive components with geometrical parameters as variables. Compared to conventional training methods, the proposed method allows better accuracy in challenging applications involving high-order transfer functions, wide frequency range, and large geometrical variations. Three examples including parametric modeling of slotted patch antennas, bandstop microstrip filters, and bandpass coupled-line filters are examined to demonstrate the validity of this technique.      

一种基于Laplacian语音模型的语音增强算法

本文提出了一种新的基于Laplacian语音模型的语音增强算法。首先,在假定语音和噪声的短时DCT系数分别服从Laplacian和Gaussian分布的基础上,推导了最小均方误差意义下的语音信号短时DCT系数估计;然后,根据语音存在概率估计,提出了语音信号短时DCT系数估计的修正因子。在增强算法中,提出了面向判决的Laplacian语音模型参数估计和基于Laplacian语音模型的改进最小量控制递归平均(IMCRA)噪声估计算法。仿真结果表明,本文算法不仅在噪声抑制性能方面优于近两年国际上提出的几种基于Gaussian语音模型的语音增强算法,而且在增强语音质量方面也具有更好的性能。     

AM/FM signal estimation with micro-segmentation and polynomial fit

Amplitude and phase estimation of AM/FM signals with parametric polynomial representation require the polynomial orders for phase and amplitude to be known. But in reality, they are not known and have to be estimated. A well-known method for estimation is the higher-order ambiguity function (HAF) or its variants. But the HAF method has several reported drawbacks such as error propagation and slowly varying or even constant amplitude assumption. Especially for the long duration time-varying signals like AM/FM signals, which require high orders for the phase and amplitude, computational load is very heavy due to nonlinear optimization involving many variables. This paper utilizes a micro-segmentation approach where the length of segment is selected such that the amplitude and instantaneous frequency (IF) is constant over the segment. With this selection first, the amplitude and phase estimates for each micro-segment are obtained optimally in the LS sense, and then, these estimates are concatenated to obtain the overall amplitude and phase estimates. The initial estimates are not optimal but sufficiently close to the optimal solution for subsequent processing. Therefore, by using the initial estimates, the overall polynomial orders for the amplitude and phase are estimated. Using estimated orders, the initial amplitude and phase functions are fitted to the polynomials to obtain the final signal. The method does not use any multivariable nonlinear optimization and is efficient in the sense that the MSE performance is close enough to the Cramer–Rao bound. Simulation examples are presented.     

Feedback cancellation in hearing aids: results from a computersimulation

Feedback cancellation in hearing aids involves estimating the feedback signal and subtracting it from the microphone input signal. The feedback-cancellation system described updates the estimated feedback path whenever changes are detected in the feedback behavior. When a change is detected, the normal hearing-aid processing is interrupted, a pseudorandom probe signal is injected into the system, and a set of filter coefficients is adjusted to give an estimate of the feedback path. The hearing aid is then returned to normal operation with the feedback-cancellation filter as part of the system. Two approaches are investigated for computing the filter coefficients: a least-mean square (LMS) adaptive filter and a Wiener filter. Test results are presented for a computer simulation of an in-the-ear (ITE) hearing aid. The simulation results indicate that more than 10 dB of cancellation can be obtained and that the Wiener filter is more effective in the presence of strong interference     

基于CPLD的FIR滤波器的快速实现

介绍了用CPLD实现高精度高速度FIR数字滤波器的基本方法,可以方便地调整滤波器的阶数和系数,适合不同的应用。时序分析表明,该设计在系数量化数据宽度为20bit时可工作于40MHz以上的时钟频率。用设计软件对X-Ray取样信号进行功能仿真,并与Matlab仿真结果进行比较。结果表明该设计是可靠的,可以满足一些高精度实时系统如X-Ray数字谱仪的需求。     

Signature sequence adaptation for DS-CDMA with multipath

Joint transmitter-receiver adaptation is studied for the reverse link of a direct sequence-code division multiple access system with short signature sequences. The signature for a particular user is computed at the receiver and transmitted back to the transmitter via a feedback channel. A reduced-rank transmitter adaptation scheme is presented in which the signature is constrained to lie in a lower dimensional subspace. This allows a tradeoff between system performance and the number of estimated parameters. Analytical and simulation results show that adaptation of relatively few transmitter coefficients can lead to significant performance improvements. Adaptive algorithms are derived for estimating the transmitter coefficients in the presence of multipath. We consider both collective optimization, in which the users adapt together to improve a global system performance criterion, and individual optimization, in which the signature for a particular user is adapted to optimize individual performance. Numerical results are presented, which show that both individual and collective joint transmitter-receiver adaptation can effectively preequalize the channel and avoid interference at high loads     

Kinetics of structural and phase transformations in thin SiO<Subscript>x</Subscript> films in the course of a rapid thermal annealing

Infrared spectroscopy and analysis of photoluminescence spectra have been used to study variations in the composition of the oxide phase in a SiO_x film and the precipitation of the Si phase in the course of a rapid thermal annealing for 1–40 s at temperatures of 500–1000°C. Kinetics of phase segregation has been observed for the first time at temperatures of 600–700°C: an increase in the amount of precipitated silicon as the annealing duration increases followed by an eventual leveling off. The phase separation is brought to completion in a time as short as 1 s at temperatures higher than 900°C. The diffusion coefficient is estimated in the context of a model of the diffusion-controlled formation of Si nanoparticles. The obtained values of the diffusion coefficient exceed, by five to ten orders of magnitude, those of the silicon diffusion coefficients in SiO₂ and Si and are comparable to the diffusion coefficients of the oxygen contained in these structures. It is assumed that oxygen mobility forms the basis for the mechanism of structural and phase transformations in the SiO_x layers and for the formation of Si nanoparticles in the course of annealing.     

Diffeomorphic image registration of diffusion MRI using spherical harmonics

Nonrigid registration of diffusion magnetic resonance imaging (MRI) is crucial for group analyses and building white matter and fiber tract atlases. Most current diffusion MRI registration techniques are limited to the alignment of diffusion tensor imaging (DTI) data. We propose a novel diffeomorphic registration method for high angular resolution diffusion images by mapping their orientation distribution functions (ODFs). ODFs can be reconstructed using q-ball imaging (QBI) techniques and represented by spherical harmonics (SHs) to resolve intra-voxel fiber crossings. The registration is based on optimizing a diffeomorphic demons cost function. Unlike scalar images, deforming ODF maps requires ODF reorientation to maintain its consistency with the local fiber orientations. Our method simultaneously reorients the ODFs by computing a Wigner rotation matrix at each voxel, and applies it to the SH coefficients during registration. Rotation of the coefficients avoids the estimation of principal directions, which has no analytical solution and is time consuming. The proposed method was validated on both simulated and real data sets with various metrics, which include the distance between the estimated and simulated transformation fields, the standard deviation of the general fractional anisotropy and the directional consistency of the deformed and reference images. The registration performance using SHs with different maximum orders were compared using these metrics. Results show that the diffeomorphic registration improved the affine alignment, and registration using SHs with higher order SHs further improved the registration accuracy by reducing the shape difference and improving the directional consistency of the registered and reference ODF maps.